PSV-12 Impact of grain processing and undegradable fiber on chewing behavior and feed sorting of finishing beef cattle
Bibliographic record
Abstract
Abstract The objective was to investigate the effects of processing index (PI, weight after processing/weight before processing × 100) of barley grain and dietary undegradable fiber (uNDF, 240 h of incubation in rumen) concentration on chewing behavior (3 days, video recording) and feed sorting of finishing beef cattle. Six ruminally cannulated beef heifers (BW=715 kg) were used in a 6 × 6 Latin square design with 3 PI (65, 75 and 85%; fine, medium, coarse, respectively) × 2 uNDF concentrations (low and high; 4.6 vs. 5.6% of DM) factorial arrangement. Heifers were fed ad libitum a TMR consisting of 10% barley silage (low uNDF) or 5% silage and 5% chopped straw (high uNDF), 87% dry-rolled barley grain, and 3% vitamin and mineral supplement. An interaction of PI with uNDF occurred (P < 0.01) for DM intake, ruminating and total chewing time. Intake of DM (kg/d) did not differ (12.1) between low and high uNDF diets with 65 or 75% PI, whereas it was greater (P < 0.05) for high (12.7) than low (12.1) uNDF diets with 85% PI. Eating time (min/d) was not affected by PI but eating time (106 vs. 95 min/d; P = 0.03) and eating index (9.3 vs. 8.0 min/kg DM; P = 0.02) were greater with high than low uNDF diets. Ruminating (305 vs. 258 min/d) and total chewing (406 vs. 357 min/d) times were greater (P < 0.05) with high than low uNDF at 65% PI, with no effect of uNDF at 75 and 85% PI. Moreover, no interaction between PI and uNDF and no effect of PI on sorting index was observed. Heifers fed high vs. low uNDF diets sorted (P < 0.01) against long particles (>19 mm). These results suggest that when cattle are fed finely processed barley, increasing uNDF concentration of the diet may promote chewing and benefit rumen health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".